Evidence map›Paper›PMID 22056214›Full record

ArticleAtherosclerosis2012

Weight change modulates epicardial fat burden: a 4-year serial study with non-contrast computed tomography.

Ryo Nakazato, Ronak Rajani, Victor Y Cheng, Haim Shmilovich, Rine Nakanishi, Yuka Otaki, Heidi Gransar, Piotr J Slomka, Sean W Hayes, Louise E J Thomson and 7 more

Abstract read
In one paragraph

Article in Atherosclerosis, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 1 pooled it
5.5field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 1 synthesis or guideline pooled it, 77 citations in OpenAlex.

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  12. Epicardial adipose tissue as a mediator of cardiac arrhythmias.American journal of physiology. Heart and circulatory physiology · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors at 6 institutions in 1 country.

Ryo NakazatoDepartments of Imaging (Division of Nuclear Medicine), Medicine (Division of Cardiology), and the Cedars-Sinai Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
Ronak Rajani
Victor Y Cheng
Haim Shmilovich
Rine Nakanishi
Yuka Otaki
Heidi Gransar
Piotr J Slomka
Sean W Hayes
Louise E J Thomson
John D Friedman
Nathan D Wong
Leslee J Shaw
Matthew Budoff
Alan Rozanski
Daniel S Berman
Damini Dey
Cedars-Sinai Medical Center · USUniversity of California, Los Angeles · USEmory University · USSt. Luke's-Roosevelt Hospital Center · USThe Lundquist Institute · USUniversity of California, Irvine · US

Funding

ZONA-FREE HAMSTER OVA ASSAY AS AN INDICATOR OF MALE FERTILITYM01RR000425 · NCRR · LUNDQUIST INSTITUTE FOR BIOMEDICAL INNOVATION AT HARBOR-UCLA MEDICAL CENTER · PI ANDERSON, GAIL V · 1985 to 2011
$74.2M
AUTOMATIC QUANTITATIVE CT IMAGING OF PERICARDIAL FAT: A NOVEL ISCHEMIA PREDICTORR21EB006829 · NIBIB · CEDARS-SINAI MEDICAL CENTER · PI DEY, DAMINI · 2008 to 2009
$441k
NCRR NIH HHS M01 RR000425NCRR NIH HHS M01-RR00425NIBIB NIH HHS R21 EB006829NIBIB NIH HHS R21EB006829
6 · The paper itself

Abstract

introductionEpicardial fat volume (EFV) is linked to cardiovascular event risk. We aimed to investigate the relationships between EFV and weight change.

methodsFrom the EISNER (Early Identification of Subclinical Atherosclerosis using Non-invasive Imaging Research) Registry with baseline and follow-up coronary calcium scans (1248 subjects), we selected a cohort of 374 asymptomatic subjects matched using age decade, gender and coronary calcium score (CCS) as a measure of subclinical cardiovascular risk, who underwent 2 scans at an interval of 4.1±0.4 years. Using semi-automated validated software, pericardial contours were generated on all slices by spline interpolation from 5 to 10 control points. EFV was computed as fat volume within the pericardial contours. Weight gain/loss was defined as >5% change.

resultsAt baseline, EFV was moderately correlated to weight, body mass index (BMI) and waist circumference (r=0.51, 0.41 and 0.50, p<0.0001). EFV change was weakly correlated to change in weight (r=0.37, p<0.0001), BMI (r=0.39, p<0.0001) and waist circumference (r=0.21, p=0.002). On multivariable linear regression analysis, weight change [β=1.2, 95% confidence interval (CI) 0.9-1.5, p<0.001], BMI change (β=1.2, 95% CI 0.9-1.5, p<0.001), gender (β=-6.4, 95% CI -10.9 to -1.8, p=0.006) and hypertension (β=4.7, 95% CI 0.5-9.0, p=0.03) predicted EFV change. EFV decreased in 54 subjects with weight loss and increased in 71 subjects with weight gain (-2.3±21.1% vs. 23.3±24.4%, p<0.001).

conclusionsEFV is related to body weight, BMI and waist circumference. Reduction in weight may stabilize or reduce EFV, while weight gain may promote EFV increase.

Indexed as

Tomography, X-Ray ComputedWeight GainWeight LossAdipose TissueAdultAgedAnalysis of VarianceBody Mass IndexCase-Control StudiesFemaleHumansLinear ModelsMaleMiddle AgedMultivariate AnalysisPericardium

Identifiers

PMID22056214
PMCPMC3638074
OpenAlexW2109902120

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.